## 4 Results and Discussion  
### The Basic Results  
Looking at cassava-planting input-output analysis of Table 4 in Section 3.5 and output-oriented VAR of Section 3, DEAP2.1 [29] was used to measure the planting cost of cassava among the six provinces. In the procedure, those external factors, such as environment and CPI, are excluded from consideration of its influence on the research result. Summary statistics of the sample farms were presented in Table 3 in Section 3.4. In Table 5, for the six provinces, only Guangdong DEA is efficient. _OTE_, _PTE_, and _SE_ in Guangdong all stand at 1, which is on the production frontiers. They represent optimal efficiency and thus become the benchmark for the other five provinces. The highest output of cassava in Guangdong is 1,267,065 Yuan; the lowest cost for materials and services is 186.566 Yuan; and the lowest cost for human labor is 393.178 Yuan. The data show the universality of Guangdong province's input efficiency and output efficiency in its cassava production and 12670.65 is the best output target. The other five provinces have decreased returns to scale or states in which there exists no or very low technology efficiency, along with the start of relaxation in both input and output. A phenomenon of this kind reflects an irrational structure of input and output that exists in these five provinces. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Province** & **Output (Ton/ha)** & \begin{tabular}{c} **Sales Income** \\ **(Yuan/ha)** \\ \end{tabular} & \begin{tabular}{c} **Total Production** \\ **Cost (Yuan/ha)** \\ \end{tabular} & \begin{tabular}{c} **Input Cost of Material** \\ **and Service (Yuan/ha)** \\ \end{tabular} & \
\begin{tabular}{c} **Machine Cost** \\ **(Yuan/ha)** \\ \end{tabular} &
\begin{tabular}{c} **Labor Cost** \\ **(Yuan/ha)** \\ \end{tabular} \\ \hline Guangqi & 31.94 & 17,886,40 & 13,522,05 & 5030.40 & 1350.00 & 7141.70 \\ Guangdong & 33.53 & 20,118.00 & 7447.35 & 1865.55 & 1650.00 & 3931.78 \\ Yunnan & 27.08 & 15,977.20 & 12,146.40 & 2738.85 & 1350.00 & 8057.51 \\ Hainan & 38.76 & 21,318.00 & 13,398.30 & 3016.50 & 1500.00 & 8881.74 \\ Fujian & 25.14 & 13,827.00 & 9623.55 & 2440.95 & 1500.00 & 5682.65 \\ Jiangxi & 28.97 & 17,671.70 & 10,999.50 & 3780.00 & 1350.00 & 5869.52 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Cassava production input–output analysis of six provinces in 2014. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Province** & **OTE** & **_PTE_** & _SE_ & _SE_ (drs,irs)** & **DEA** & \begin{tabular}{c} **Peer Count** \\ **Summary** \\ \end{tabular} & \
\begin{tabular}{c} **Deturb Target** \\ **Service Fee** \\ \end{tabular} &
\begin{tabular}{c} **DEA Project Value** \\ **Labor Cost** \\ \end{tabular} \\ \hline Guangqi & 0.189 & 0.344 & 0.551 & drs & NO & 12670.65 & 1865.55 & 3931.78 \\ Guangdong & 1.000 & 1.000 & 1.000 & — & YES & 5 & 12670.65 & 1865.55 & 3931.78 \\ Yunnan & 0.206 & 0.302 & 0.681 & drs & NO & 0 & 12670.65 & 1865.55 & 3931.78 \\ Hainan & 0.387 & 0.625 & 0.618 & drs & NO & 0 & 12670.65 & 1865.55 & 3931.78 \\ Fujian & 0.254 & 0.332 & 0.764 & drs & NO & 0 & 12670.65 & 1865.55 & 3931.78 \\ Jiangxi & 0.353 & 0.527 & 0.670 & drs & NO & 0 & 12670.65 & 1865.55 & 3931.78 \\ AVG & 0.398 & 0.552 & 0.714 & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Six province cassava production efficiency (DEA) in 2014. In terms of _PTE_ of five provinces, Yunnan is the lowest with 0.302, and _PTE_ of Guangxi is 0.344. _PTE_ of Hainan is lower than Guangdong with 0.625. In terms of _SE_ of the five provinces, the largest cassava-planting province, Guangxi, is the lowest _SE_ with 0.551, and the _SE_ of Fujian is relatively optimal with 0.764. Among them, Guangxi's _OTE_ stands at the lowest level of 0.189. The data show that enlarged production scale is needed to promote the _SE_ and _OTE_, with the current input staying unchanged. It shows that the cassava-production efficiency and planting management in Guangxi need to be improved.